Public Records on File.. do you ever invest in the note?

[lender_john]

I wanted to get your thoughts on loans where there is at least one public record on file.

Normally I completely avoid those for obvious reasons.

What do you think about notes where the public record was around 10 years ago and everything else looks great (for whatever your personal selection criteria may be) ?

There is a certain argument to be made that someone who recovered from bankruptcy and now works hard to be financially responsible, may be as safe or a safer bet than an average borrower.

[rajuabju]

No, absolutely not for me.

Public records are almost (but not always, I admit) BK's.

If a person has filed for BK once, and is in debt consolidation mode again, to me, they just havent been able to learn from their past experience.

I absolutely filter them out without hesitation.

[rev]

There is a certain argument to be made that someone who recovered from bankruptcy and now works hard to be financially responsible, may be as safe or a safer bet than an average borrower.

I don't know how true that argument is, but statistically, almost all populations have better performance if you eliminate the borrowers with one or more public records.
I found one that does not, A and B grade loans with high income.:
http://www.interestradar.com/analysis?CG=A&CG=B&PR=0&PR=1&MI=7&MI=8&MI=9&MI=10&MI=11&MI=12&ShowBreakdown=1

Maybe working hard to be financially responsible isn't good enough if you just don't make enough money...
Also, once you learn how easy it is to file bankruptcy and how well the system works for those seeking this type of relief, maybe you actually care even less. But I'm just hypothesizing from what I hear; I have no personal knowledge of how hard or how easy it is to go through a bankruptcy.

[faeriering]

I did have a couple notes with public records that looked good otherwise, one defaulted 7 years after their last bankruptcy filing. . . I avoid these now.

[Keltset]

I absolutely filter them out without hesitation.

Public records are bad M'Kay--- I don't invest in any with them.

[yojoakak]

All else being equal, I'd take the loan without the Public Record. But how often do you find 2 loans that are equal except for 1 thing?

In any case I've always assumed Public Records are taken into account in the FICO score.

Have I been mistaken all this time?!?

[brycemason]

Public record is just one thing among many that affects the probability of a charge off. An attractive loan along many other dimensions may still be attractive with a public record. I buy them occasionally if the math works out.

[SarahV]

If you look at the historical loan stats, the presence of a public record has a horrible effect. ROI is halved, default rate is doubled or tripled. No thanks. I am not so desperate for loans that I would buy one of those.

[brycemason]

Perhaps if you look *solely* at public record, it has a tremendous effect. But if you look at dozens of factors simultaneously, you will come to realize they all share variance. The unique predictive power of public record is  +0.045 to the probability of a charge off.

[SarahV]

If you look at it that way, how could you ever come up with useful filters? Every one single criteria has a relatively small effect. But you need to pick *something* to filter on (if you're using filters, which I am). So why not filter out things with a strong negative effect like that?

[brycemason]

I don't use filters. I calculate the probability of a charge off event for every loan, compare it to the interest rate, and then generate a list of all loans available for investment ordered by expected profit. I have a threshold value where I would be willing to invest in any loan above a certain expected profit. Back testing this strategy suggests returns in the top 10% of any strategy I have come across and has a huge upside compared to a filter strategy: on any given day I could find dozens of loans in which to invest.

[william]

I don't use filters. I calculate the probability of a charge off event for every loan, compare it to the interest rate, and then generate a list of all loans available for investment ordered by expected profit. I have a threshold value where I would be willing to invest in any loan above a certain expected profit. Back testing this strategy suggests returns in the top 10% of any strategy I have come across and has a huge upside compared to a filter strategy: on any given day I could find dozens of loans in which to invest.

Interesting but it sounds very time consuming.

Currently I'm not invested in loans with public records, and don't ever plan on it. As Sarah so wonderfully put it  "I am not so desperate for loans that I would buy one of those."

[Keltset]

Brycemason's method is actually very quick once you have the programs written and in place to go through the loans and it's much more effective then using a blanket filter through LC or something like that. It just takes some time to initially put it together then the system is pretty much set and forget with a quick glance over the note before you pull the buy trigger.

[brycemason]

I spent the first part of 2012 making the programs and algorithms, and have refined and tested them (with $35k of my own money) this year also. I'm eager to launch a new website service where people will be able to take advantage of my work later in the month--at least a beta version.

It only takes about 2 minutes to make a beautiful Excel sheet with my picks, and then another handful of minutes to make the investment. Couldn't imagine doing it any other way.

When the API comes online I will make a server service that continuously runs my algorithms and automatically invests any idle balances. Or perhaps I will work with others who have developed such systems already. There's some good stuff brewing!

If you get enough loans in which to invest with a strict filter strategy, that's great. It's hard to scale up a filter strategy to sell, though, so that there's enough "product" for all your subscribers.

[viking]

I don't use filters. I calculate the probability of a charge off event for every loan, compare it to the interest rate, and then generate a list of all loans available for investment ordered by expected profit. I have a threshold value where I would be willing to invest in any loan above a certain expected profit. Back testing this strategy suggests returns in the top 10% of any strategy I have come across and has a huge upside compared to a filter strategy: on any given day I could find dozens of loans in which to invest.

May I ask what you mean by "returns in the top 10% of any strategy"? What is the back-tested return and what time-period did you use for the back testing?

Would you mind sharing how you calculate the probability?

In order to calculate a probability wouldn't you need parameters such as "public records", "employment length", "number of credit inquiries", etc?
If so, wouldn't that be similar to creating multiple filters and applying them all to the available loans?
For example:
Filter 1 => 5 loans (ROI=16%)
Filter 2 => 10 loans (ROI=10%)
Filter 3 => 5 loans (ROI= 14%)
Total 20 loans and ROI = (5*16+10*10+5*14)/20=12.5%